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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Salt Hydrate Eutectic Thermal Energy Storage for Building Thermal Regulation (Final Technical Report)

Thermal energy storage is anticipated to play an important role in developing the power grid of the future - a power grid that meets increasing demands of users, is resistant to disruptions, but also allows for greater penetration of renewable resources. Specifically, thermal energy storage materials can be integrated into HVAC systems and building envelopes, where they can be used to shift power demands for building climate control from periods of peak demand to periods of low demand. Phase change materials (PCMs) are compelling as low-cost, high energy density thermal energy storage materials for building thermal management. However, there is a lack of high performance low-cost PCMs within the specific temperature ranges which would most effectively allow for power load shifting. Inorganic salt hydrates represent a promising class of PCMs, but their inherent limitations cause them to be currently unavailable for reliable building applications. The overarching goals of this research effort are to: 1) Discover low-cost, high volumetric density salt hydrate eutectic PCMs to store low-quality heat (10 to 40 °C); 2) Introduce a high thermal conductivity matrix to reduce the time constant for energy storage to ~0.1 to 1 hr, incorporate nucleation catalysts to decrease undercooling, and utilize microencapsulation and shape stabilization approaches, minimizing moisture loss/gain, mitigating phase separation, and maintaining stable melting behavior over the lifetime of the compounds; 3) Evaluate the impact these systems have on peak load shifting, and the potential for overall energy savings under different climatic scenarios and building configurations. These goals will be achieved by an integrated research program consisting of six cohesive research subtasks: 1) Materials discovery of eutectic salt hydrate PCMs by using computationally predicted thermodynamic equilibria, coupled with high-throughput experimental validation, 2) Rapid experimental screening of nucleation catalysts identified through robust computational databases, 3) Embedding salt hydrate PCM into a low cost and scalable high conductivity matrix, 4) Microencapsulation of salt hydrate microspheres using hybrid inorganic-polymer microencapsulation approach, 5) Shape stabilization by thermoreversible salt hydrate salogels, and 6) Analysis of end-use using thermal simulations, and characterization of mock-up energy storage finished components.

25 ENERGY STORAGE↗
DOE OSTI1969

Application of Nuclear Technology to Art Identification Problems: First Annual Report

Throughout the centuries, as man has become increasingly affluent, his interest in antiquities and objects of art, and the price he has been willing to pay for them, has increased. Inevitably, one result has been to attract the unscrupulous to the production and sale of counterfeit paintings, sculptures, and other works of art. The skill of forgers varies but often is highly sophisticated. However, dealers, museum curators, and other experts have also become more skillful in the detection of forgeries. Scientific tools of increasing sensitivity and sophistication have gradually been applied to the examination of the materials of art and archaeology. Such tools frequently support and render more reliable the judgment of the experts. The quality of forgeries may improve further as their makers become acquainted with the new methods of detection and in turn learn to circumvent or confound the methods. Therefore, the development of still more advanced methods of examination has great utility in the art world. This is particularly true if the ultimate effect is to make circumvention of the methods of examination so costly that the economic incentives for producing forgeries may be substantially reduced, if not eliminated.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Plant sulfate transporter protein sequences for phylogenetic analysis

Sulfur is an essential macronutrient that supports plant growth, development, and responses to environmental stress. Sulfate is the predominant inorganic form of sulfur in soils, and its uptake by roots and translocation to shoots are facilitated by the sulfate transporter (SULTR) family of proteins. Although the first plant SULTR gene was identified nearly three decades ago, several subfamily members, particularly those in the expansive and angiosperm-specific SULTR3 group, remain poorly characterized. To support comprehensive phylogenetic and sequence-based analyses, we compiled a curated dataset of 262 SULTR protein sequences from 22 plant species spanning the evolutionary breadth of land plants. This collection includes representatives from two basal lineages, two early-divergent angiosperms, six monocots, and ten dicots. All sequences were extracted from genome assemblies available in Phytozome v13 (Joint Genome Institute) and manually curated, with cross-referencing to additional databases such as NCBI when needed. This dataset provides a valuable resource for reconstructing the evolutionary history of the SULTR family, with particular emphasis on the diversification of SULTR3 transporters in flowering plants. This resource may also support functional annotation, comparative genomics, and structural modeling of sulfate transport proteins.

CBI↗
DOE OSTI2023

Climatology of aerosol properties at an atmospheric monitoring site on the northern California coast

Between April 2002 and June 2017, the Global Monitoring Laboratory (GML) of the National Oceanic and Atmospheric Administration (NOAA) made continuous measurements of a suite of in situ aerosol optical properties at a long-term monitoring site near Trinidad Head (THD), California. In addition to aerosol optical properties, between 2002–2006 a scanning humidograph system was operated, and inorganic ion and total aerosol mass concentrations were obtained from filter measurements. A combined analysis of these datasets demonstrates consistent patterns in aerosol climatology and highlights changes in sources throughout the year. THD is predictably dominated by sea salt aerosols; however, marine biogenic aerosols are the largest contributor to PM1 in the warmer months. Additionally, a persistent combustion source appears in the winter, likely a result of wintertime home heating. While the influences of local anthropogenic sources from vehicular and marine traffic are visible in the optical aerosol data, their influence is largely dictated by the wind direction at the site. Comparison of the THD aerosol climatology to that reported for other marine sites shows that the location is representative of clean marine measurements, even with the periodic influence of anthropogenic sources.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Surfactants and cloud droplet activation: A systematic extension of Köhler theory based on analysis of droplet stability

The activation of aerosol particles to form cloud droplets, a necessary first step in cloud formation, controls much of the impact that aerosols have on clouds and climate. Recently, there has been a surge of interest in extending the Köhler theory of cloud droplet activation to include surface active (typically organic) as well as water-soluble (typically inorganic) aerosol components, but a systematic framework for doing this has yet to be developed. Here, we apply a droplet stability analysis to this end. Ideal and Szyszkowski–Langmuir surfactant models are analyzed to demonstrate the new approach, but the underlying theoretical framework is fundamental and model free. A key finding is that superficial densities at the cloud activation threshold (Köhler maximum) are significantly sub-monolayer, with fractional coverage ranging from 69% to 85% for the organic compounds and mixtures studied. The result, significant for model inventories of cloud condensation nuclei, is a weakening of the surfactant effect relative to expectations based on bulk sample measurements. Analytical results are obtained for the loci of Köhler maxima and applied to aerosol mixtures containing an arbitrary number of water-soluble and surfactant components.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Inorganic characterization of switchgrass biomass using laser-induced breakdown spectroscopy

The inorganic characterization of 74 samples of switchgrass using laser-induced breakdown spectroscopy (LIBS) was undertaken. Determination of ash and inorganic elements content in biomass materials is vital for feedstock screening for bioconversion processes. Hierarchical models using principal component analysis (PCA) and partial least square analysis (PLS) were used to determine the presence of specific elemental micronutrients that are important in determining plant health for robust biomass production. LIBS uses a 532 nm laser with 45 mJ of laser power to excite the samples of switchgrass plant material and the emission of all the elements present in the plant samples were recorded in single spectra with a wide wavelength range of 200–800 nm. The results were compared to the laboratory standard technique, e.g., ICP-OES technique, to determine the true values for major micronutrients such as, silicon (Si), potassium (K), calcium (Ca), magnesium (Mg), phosphorus (P), and sulfur (S). Overall, our objectives were: 1) To determine the spectral features of switchgrass containing different amounts of these elements and 2) To examine the viability of this technique for determining the quality of the feedstock in terms of its inorganic composition. Cross-validation results showed that the broad-based model developed is promising for inorganics prediction in switchgrass. The LIBS validation prediction for the micronutrient elements mentioned here have been obtained. The regression coefficients for Si, were obtained to be 0.995, 0.994 for calibration and validation respectively, in case of Ca the regression coefficients were, 0.994 and 0.992 for calibration and validation. Similarly, in the case of Mg and K these were calculated to be 0.992 and 0.985, and 0.994 and 0.993 respectively. The regression coefficients are not as good as those for the elements mentioned, in case of the two elements S and P. They are 0.957, and 0.878, and 0.952 and 0.894 respectively for calibration, validation for the two elements. This demonstrates that LIBS-based techniques are inherently well suited for diverse environmental applications. Furthermore, LIBS along with PLS model can show capability in determining the viability of switchgrass as a biomass in the production of biofuels and survivability of switchgrass in processes associated with climate change. LIBS can help determining which switchgrass would be appropriate for a specific conversion process that favors low ash content overall or low value of specific inorganics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Optimizing the Solvent Reorganization Free Energy by Metal Substitution for Nanocage Catalysis

The supramolecular capsule Ga 4 L 6 12– has been found to catalyze a number of important chemical reactions, but the close proximity of a poorly organized external solvent environment can serve as an impediment to the reaction chemistry. Here, using ab initio molecular dynamic calculations and electric field analyses, we find that metal substitution of indium for gallium lowers the total and electrostatic activation barriers by ~3–4 kcal/mol in water solvent. Using an energy decomposition analysis of the interaction of water solvent with the metal vertices, we find that Pauli repulsion between the metal and water decreases, allowing the water coordination with the metal to increase, upon substitution of In for Ga. We therefore determine that the stabilization of the transition state is due to a better arrangement of water molecules around the metal vertices of In 4 L 6 12– and provides a proof of concept of how to redesign the nanocage scaffold in order to reduce the solvent reorganization energy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Chemo-Enzymatic Synthesis of Long-Chain Oligosaccharides for Studying Xylan-Modifying Enzymes

Plant research is hampered in several aspects by a lack of pure oligosaccharide samples that closely represent structural features of cell wall glycans. An alternative to purely chemical synthesis to access these oligosaccharides is chemo-enzymatic synthesis using glycosynthases. These enzymes enable the ligation of oligosaccharide donors, when activated for example as α-glycosyl fluorides, with suitable acceptor oligosaccharides. Herein, the synthesis of xylan oligosaccharides up to dodecasaccharides is reported, with glycosynthase-mediated coupling reactions as key steps. The xylo-oligosaccharide donors were protected at the non-reducing end with a 4-O-tetrahydropyranyl (THP) group to prevent polymerization. Installation of an unnatural 3-O-methylether substituent at the reducing end xylose of the oligosaccharides ensured good water solubility. Biochemical assays demonstrated enzymatic activity for the xylan acetyltransferase XOAT1 from Arabidopsis thaliana, xylan arabinofuranosyl-transferase XAT3 enzymes from rice and switchgrass, and the xylan glucuronosyltransferase GUX3 from Arabidopsis thaliana. In case of the glucuronosyltransferase GUX3, MALDI-MS/MS analysis of the reaction product suggested that a single glucuronosyl substituent was installed primarily at the central xylose residues of the dodecasaccharide acceptor, demonstrating the value of long-chain acceptors for assaying biosynthetic glycosyltransferases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Raman Microscopy Analysis of Wyoming CarbonSAFE Pilot Well Thin Sections for Mineralogy and Organic Matter Characterization

Scanning confocal Raman microspectroscopy (RMS) was used to analyze thin sections for inorganic mineral content and for evaluation of organic material (OM). Thin sections were selected from a stratigraphic test well core in the Powder River Basin, Wyoming under the Wyoming CarbonSAFE project. The well was analyzed with a variety of rock and fluid characterization techniques to determine the feasibility of a commercial-scale CO2 storage site. RMS complements other analyses, including traditional petrography, SEM, porosity and permeability, and XRD For this aspect of the study, RMS is especially important in the evaluation of OM in sealing lithologies. At prospective geologic CO2 storage sites, it is imperative to assess the unconventional oil and gas potential of seals to ensure that any future development would not compromise the integrity of the seals. Whole-slide mineralogical surveys were performed on thin sections from various shale and sandstone formations. Surveys were analyzed with Direct Classical Least Squares to identify and quantify minerals. The location and concentration of minerals was color-coded and overlaid on optical images for visualization of the distribution of minerals. Dense hyperspectral Raman mapping of OM was performed on five thin sections. Eleven spectral parameters diagnostic of organic type and thermal maturity were used to train a Partial Least Squares (PLS) calibration against a set of artificially matured samples spanning the pre- to mid-oil window. The PLS was applied to the study set and a post-mature set. Additionally, the PLS was applied to each point in hyperspectral maps for visualization of trends in maturity across sample sets and discrimination of organic matter types within a given map. In inorganic surveys on thin sections, a total of 14 unique inorganic minerals were identified in Raman spectra including quartz, dolomite, calcite, hematite and anhydrite. Shale thin sections tended to be dominated by organic material. OM was often observed mixed with inorganic minerals. Sand- and mudstones were dominated by inorganic minerals. The PLS extrapolated the post-mature set to reflectances >1.2%. The study set ranged from very immature to postmature in the median of map fit-peak parameters. However, point maturity maps indicate that matrix OM in all study samples is immature and that discreet organic particles selected for mapping, which may be inertinites, bias medians towards more-mature. The work demonstrates the capabilities of RMS to perform both whole-slide mineralogy and OM analysis with applications to formation evaluation in oil & gas, carbon sequestration and mining. Here, analysis of sealing formations in the well indicates high levels of immature organic matter that would not be a viable target for future oil production that could compromise the CO2 storage site. The work brings together diverse disciplines from geology and petrography to analytical chemistry, big data and microscopy.

Myers, Grant↗
DOE OSTI2021

Exploring Causal Physical Mechanisms via Non-Gaussian Linear Models and Deep Kernel Learning: Applications for Ferroelectric Domain Structures

Rapid emergence of multimodal imaging in scanning probe, electron, and optical microscopies has brought forth the challenge of understanding the information contained in these complex data sets, targeting the intrinsic correlations between different channels, and further exploring the underpinning causal physical mechanisms. Here, we develop such an analysis framework for Piezoresponse Force Microscopy. We argue that under certain conditions, we can bootstrap experimental observations with the prior knowledge of materials structure to get information on certain nonobserved properties, and demonstrate linear causal analysis for PFM observables. We further demonstrate that the strength of individual causal links between complex descriptors can be ascertained using the deep kernel learning (DKL) model. In this DKL analysis, we use the prior information on domain structure within the image to predict the physical properties. This analysis demonstrates the correlative relationships between morphology, piezoresponse, elastic property, etc., at nanoscale. The prediction of morphology and other physical parameters illustrates a mutual interaction between surface condition and physical properties in ferroelectric materials. Overall, this analysis is universal and can be extended to explore the correlative relationships of other multichannel data sets, and allow for high-fidelity reconstruction of underpinning functionalities and physical mechanisms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Durable, pure water–fed, anion-exchange membrane electrolyzers through interphase engineering

Anion-exchange membrane water electrolyzers (AEMWEs) promise scalable, low-cost hydrogen production but are limited by the electrochemical instability of their anode ionomers. We report interphase engineering using inorganic-containing molecular additives that coassemble with ionomer, enabling pure water-fed AEMWEs to operate with a degradation rate <0.5 millivolt per hour at 2.0 amperes per square centimeter and 70°C-a >20-fold durability improvement. Analysis of different additives and ionomers shows that the stabilization mechanism involves cross-links between metal oxo/hydroxo oligomers and ionomers. Under operation, the inorganic additive enriches, forming an interphase near the water-oxidation catalyst that passivates the anode ionomer against continuous degradation while maintaining mechanical integrity and hydroxide conductivity. This additive-based interphase-engineering strategy provides a path to durable AEMWEs that operate without supporting electrolytes and is adaptable across diverse catalysts and ionomers for electrochemical technologies.

Hou, Shujin↗
DOE OSTI2024

Modeling delayed thermal runaway in nitric acid-soaked cat litter mixed with radioactive waste

Thermal ignition of radioactive waste within a 55-gallon drum was simulated by using a pressure-dependent waste decomposition model (Hobbs et al. in Process Saf Environ Prot https://doi.org/10.1016/j.psep.2022.09.047, 2022) calibrated with data from full-scale drum experiments (Parker et al. in The thermolytic response of a surrogate RNS waste mixture at the drum scale. Los Alamos National Laboratory Report LA-UR-16-21760, 2016) and validated with experiments from multiple laboratories (Hobbs et al. in Thermal analysis of aged nitric acid-soaked kitty litter in TRU waste drums-23370.WM2023 Conference, Phoenix, AZ, 2023). The acceleration of nitric acid chemistry reacting with an organic cat litter leading to thermal ignition was likely triggered by a restricted vent in the drum. Here, we address whether the form of the rate equation in (Hobbs et al. in Process Saf Environ Prot https://doi.org/10.1016/j.psep.2022.09.047, 2022) is sufficient to extrapolate thermal ignition within aged drums of similar content that have been stored in Texas for over nine years by investigating four different reaction rate forms for waste decomposition. A critical reaction rate reduction analysis is performed on each of these models to determine if delayed thermal runaway within vented aged waste is possible after nine years. We found that a pressure-dependent first-order rate expression not only predicted the accidental ignition of the waste drum, but the form also matches multiple experiments from different laboratories. Even though the waste composition decreases over time, the model predicts that acceleration leading to thermal runaway is possible if the waste is confined, even after 9 years. In conclusion, waste containing oxidizers such as nitric acid should not be mixed with organic adsorbents, especially if the waste is confined.

cookoff↗
DOE OSTI2020

Evidence of Alpha Radiolysis in the Formation of a Californium Nitrate Complex

Well-characterized complexes of transplutonium elements are scarce because of the experimental challenges of working with these elements and the rarity of the isotopes. This leads to a lack of structural and spectroscopic data needed to understand the nature of chemical bonds in these compounds. In this work, the synthesis of Cf(DOPO q ) 2 (NO 3 )(py) (DOPO q =2,4,6,8-tetra-tert-butyl-1-oxo-1H-phenoxazin-9-olate; py=pyridine) is reported, in which the nitrate anion is hypothesized to form through the α-radiolysis-induced reaction of pyridine and/or the ligand. Here, computational analysis of the electronic structure of the complex reveals that the Cf III –ligand interactions are largely ionic.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

High-Throughput Screening and Accurate Prediction of Ionic Liquid Viscosities Using Interpretable Machine Learning

Ionic liquids (ILs) are a novel group of green solvents with great promise for various industrial applications, including carbon capture and lignocellulosic biomass deconstruction. However, the use of ILs at the industrial scale remains challenging due to their high viscosities at ambient temperatures. To develop ILs with lower viscosities, a systematic study of their quantitative structure–property relationship (QSPR) is desirable. Here, we developed four machine learning (ML) models to predict viscosity at various temperature and pressure ranges, trained over a wide range of ILs consisting of various cationic and anionic families. ML methods including two-factor polynomial regression (two-factor PR), support vector regression (SVR), feed-forward neural networks (FFNN), and categorical boosting (CATBoost) were developed based on features that have proven useful in previous ML studies: COSMO-RS (conductor-like screening model for real solvents)-derived surface screening charge densities (sigma profiles). FFNN and CATBoost were the most accurate in predicting IL viscosities with lower average absolute relative deviation and higher R2 values on the test set. Tanimoto similarity scores were calculated to characterize the chemical space and structural similarity of the investigated ions. Furthermore, SHapley Additive exPlanation (SHAP) analysis was employed to interpret the ML results. Temperature, the polar area of ILs, and the nonpolar regions of ions are key features that influence the viscosity predictions. Importantly, the IL viscosity prediction here is the most accurate reported to date.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Grid resolution requirement of chemical explosive mode analysis for large eddy simulations of premixed turbulent combustion

Full Article Figures & data References Citations Metrics Reprints & Permissions Read this article Abstract The grid resolution requirement for trustworthy Chemical Explosive Mode Analysis (CEMA) in Large Eddy Simulation (LES) of premixed turbulent combustion is proposed. Explicit filtering, to emulate the effect of the LES filter, is applied to one-dimensional laminar flame and three-dimensional planar turbulent flames across a wide range of Karlovitz numbers (5 - 239). The identification of the flame front by CEMA is found relatively insensitive to the cell size (Δ), while the combustion mode identification shows more significant sensitivity. Specifically, increasing Δ falsely enhances the auto-ignition and local extinction modes and suppresses the diffusion-assisted mode. Limited dependence of the CEMA performance on the turbulent combustion regime (Karlovitz number) is observed. A simple grid size criterion for reliable CEMA mode identification in LES is proposed as Δ ≲ δ L /2; The criterion can be relaxed to Δ ≲ δ L in the laminar flame limit. Furthermore, theoretical analysis is conducted on an idealised chemistry-diffusion system. The effects of the filtering process and turbulence on the local combustion mode are demonstrated, which is consistent with the numerical observations. Further, by incorporating turbulent combustion models in CEMA, potential improvement in identifying local combustion modes can be expected.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Persistent Protein Motions in a Rugged Energy Landscape Revealed by Normal Mode Ensemble Analysis

Proteins are allosteric machines that couple motions at distinct, often distant, sites to control biological function. Low-frequency structural vibrations are a mechanism of this long-distance connection and are often used computationally to predict correlations, but experimentally identifying the vibrations associated with specific motions has proved challenging. Spectroscopy is an ideal tool to explore these excitations, but measurements have been largely unable to identify important frequency bands. The result is at odds with some previous calculations and raises the question what methods could successfully characterize protein structural vibrations. Here we show the lack of spectral structure arises in part from the variations in protein structure as the protein samples the energy landscape. However, by averaging over the energy landscape as sampled using an aggregate 18.5 μs of all-atom molecular dynamics simulation of hen egg white lysozyme and normal-mode analyses, we find vibrations with large overlap with functional displacements are surprisingly concentrated in narrow frequency bands. These bands are not apparent in either the ensemble averaged vibrational density of states or isotropic absorption. However, in the case of the ensemble averaged anisotropic absorption, there is persistent spectral structure and overlap between this structure and the functional displacement frequency bands. We systematically lay out heuristics for calculating the spectra robustly, including the need for statistical sampling of the protein and inclusion of adequate water in the spectral calculation. The results show the congested spectrum of these complex molecules obscures important frequency bands associated with function and reveal a method to overcome this congestion by combining structurally sensitive spectroscopy with robust normal mode ensemble analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗